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# FIRST AUTHOR <EMAIL@ADDRESS>, 2022.
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#: ../source/paddlenlp.taskflow.models.sentiment_analysis_model.rst:2
msgid "sentiment\\_analysis\\_model"
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.BoWModel:1
msgid ""
"This class implements the Bag of Words Classification Network model to "
"classify texts. At a high level, the model starts by embedding the tokens"
" and running them through a word embedding. Then, we encode these "
"epresentations with a `BoWEncoder`. Lastly, we take the output of the "
"encoder to create a final representation, which is passed through some "
"feed-forward layers to output a logits (`output_layer`). :param "
"vocab_size: The vocab size that used to create the embedding. :type "
"vocab_size: int :param num_class: The num class of the classifier. :type "
"num_class: int :param emb_dim: The size of the embedding, default value "
"is 128. :type emb_dim: int. optinal :param padding_idx: The padding value"
" in the embedding, the padding_idx of embedding value will"
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.BoWModel:13
#: paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel:13
msgid "not be updated, the default value is 0."
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.BoWModel
#: paddlenlp.taskflow.models.sentiment_analysis_model.BoWModel.forward
#: paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel
#: paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel.forward
#: paddlenlp.taskflow.models.sentiment_analysis_model.SkepSequenceModel.forward
msgid "参数"
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.BoWModel:15
msgid "The output size of linear that after the bow, default value is 128."
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.BoWModel:17
msgid ""
"The output size of linear that after the fisrt linear, default value is "
"96."
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.BoWModel.forward:1
#: paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel.forward:1
#: paddlenlp.taskflow.models.sentiment_analysis_model.SkepSequenceModel.forward:1
msgid ""
"Defines the computation performed at every call. Should be overridden by "
"all subclasses."
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.BoWModel.forward:4
#: paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel.forward:4
#: paddlenlp.taskflow.models.sentiment_analysis_model.SkepSequenceModel.forward:4
msgid "unpacked tuple arguments"
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.BoWModel.forward:6
#: paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel.forward:6
#: paddlenlp.taskflow.models.sentiment_analysis_model.SkepSequenceModel.forward:6
msgid "unpacked dict arguments"
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel:1
msgid ""
"This class implements the Bag of Words Classification Network model to "
"classify texts. At a high level, the model starts by embedding the tokens"
" and running them through a word embedding. Then, we encode these "
"epresentations with a `BoWEncoder`. Lastly, we take the output of the "
"encoder to create a final representation, which is passed through some "
"feed-forward layers to output a logits (`output_layer`). :param "
"vocab_size: The vocab size that used to create the embedding. :type "
"vocab_size: int :param num_class: The num clas of the classifier. :type "
"num_class: int :param emb_dim: The size of the embedding, default value "
"is 128. :type emb_dim: int. optinal :param padding_idx: The padding value"
" in the embedding, the padding_idx of embedding value will"
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel:15
msgid "The output size of the lstm, defalut value 198."
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel:17
msgid "The direction of lstm, default value is `forward`."
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel:19
msgid "The num of lstm layer."
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel:21
msgid "The dropout rate of lstm."
msgstr ""

#: of paddlenlp.taskflow.models.sentiment_analysis_model.LSTMModel:23
msgid ""
"The pooling type of lstm. Defalut value is None, if `pooling_type` is "
"None, then the LSTMEncoder will return the hidden state of the last time "
"step at last layer as a single vector."
msgstr ""

